Qwen 3.5 397B-A17B — GB300 NVL72 vs H200
Head-to-head AI inference benchmark comparison of GB300 NVL72 (NVIDIA Blackwell) and H200 (NVIDIA Hopper) on Qwen 3.5 397B-A17B. Latency, throughput, and cost across LLM workloads. Use the chart controls below to switch sequences, precisions, and metrics — same interactions as the main inference chart.
Near the low end of the 40–187 tok/s/user interactivity band, at 77 tok/s/user on Qwen 3.5 397B-A17B: GB300 NVL72 runs 11644 tok/s/GPU at $0.06/M tokens, H200 runs 1510 at $0.26/M. GB300 NVL72 is 310% cheaper per token; GB300 NVL72 delivers 671% more tok/s/GPU.
Setting 114 tok/s/user as the target on Qwen 3.5 397B-A17B, GB300 NVL72 produces 7392 tok/s/GPU ($0.10 per million tokens) and H200 produces 1174 ($0.33). GB300 NVL72 is 232% cheaper per token; GB300 NVL72 delivers 530% more tok/s/GPU.
At 151 tok/s/user interactivity on Qwen 3.5 397B-A17B, GB300 NVL72 delivers 3829 tok/s/GPU at $0.19 per million tokens; H200 delivers 935 tok/s/GPU at $0.42. GB300 NVL72 is 121% cheaper per token; GB300 NVL72 delivers 310% more tok/s/GPU at this point. (Numbers reflect the default 8k/1k · fp8 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/gpu) | GB300 NVL72:11644.2H200:1510.0 | GB300 NVL72:7392.3H200:1174.1 | GB300 NVL72:3829.5H200:934.8 |
| Cost ($/M tok) | GB300 NVL72:$0.063H200:$0.259 | GB300 NVL72:$0.101H200:$0.335 | GB300 NVL72:$0.189H200:$0.417 |
| tok/s/MW | GB300 NVL72:5492531H200:1102201 | GB300 NVL72:3486939H200:856983 | GB300 NVL72:1806354H200:682333 |
| Concurrency | GB300 NVL72:~1299H200:~18 | GB300 NVL72:~364H200:~10 | GB300 NVL72:~61H200:~6 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.